Data Viz Gallery

Static Visualizations

A scatterplot that displays the number of athletes with sub 10 second performances across ages 18 to 40
A scatterplot that displays the team who won the NCAA Cross Country Championshps each year
A line chart showing the increase in the number of sub 4 minute milers from each university over time
A bar graph showing the count of sub 44 second 400 meter performances for each athlete
A heatmap that displays the number of steps walked each day throught the year
A tree map that displays university endowments
Dynamic Visualizations

##| include: false
#| echo: false
#| fig-width: 6
#| fig-height: 4.2


# Load data
pop_data <- readRDS("data/pop_change.rds")

state_geom <- readRDS("data/state_geom.rds")

# Create static plot
plot_demo <- ggplot(pop_data,  aes(fill = pop_category)) +
  geom_sf_interactive(
    aes(tooltip = tooltip, data_id = NAME),
    color = "white",
    linewidth = 0.1
  ) +
  geom_sf(
    data = state_geom, 
    color = "gray50", 
    fill = NA,
    linewidth = 0.3
  ) +
  scale_fill_manual(values = c("gray", "#8c510a","#bf812d", "#dfc27d","#f6e8c3", "#c7eae5","#80cdc1","#35978f", "#01665e")) +
  scale_x_continuous(expand = expansion(mult = c(0.02, 0.14))) +
  labs(
    title = "U.S. County Population Changes: 2019-2023",
    caption = "Data: U.S. Census Bureau\nViz: Tim Fulton, PhD"
  ) +
  theme_void() +
  theme(
    plot.background = element_rect(fill = "white", color = "white"),
    plot.title = element_text(size = 13, face = "bold", hjust = 0.5, margin = margin(b = 2)),
    plot.caption = element_text(size = 7, color = "black", face = "italic", hjust = 0.02),
    legend.title = element_blank(),
    legend.key.size = unit(0.25, "cm"),
    legend.text = element_text(size = 7),
    legend.position = "inside",
    legend.position.inside = c(0.91, 0.32)
  ) +
  guides(fill = guide_legend(reverse = TRUE))

# Render interactive plot
girafe(ggobj = plot_demo) %>%
  girafe_options(
    opts_hover(css = "fill:black;"), 
    opts_toolbar(saveaspng = FALSE)
  )